Tech Lead - Data Science
Trane Technologies6 months ago
Bengaluru, IndiaStaff+
Responsibilities
- Provide technical leadership for end-to-end AI/ML system development, including data ingestion, feature engineering, model deployment, and monitoring.
- Define scalable, secure, performant ML platform architecture and organizational standards.
- Evaluate, select, and integrate AI technologies, frameworks, tools, and GenAI solutions.
- Translate business requirements into ML architectures and solution roadmaps with product and domain teams.
- Oversee experimentation, versioning, deployment, monitoring, retraining, and continuous improvement across the ML model lifecycle.
- Mentor data scientists, ML engineers, and analysts and conduct reviews of ML pipelines, code, and solution designs.
- Drive MLOps workflows and partner with cross-functional teams to resolve complex ML and data pipeline issues.
- Advance best practices in AI architecture, model evaluation, documentation, data governance, compliance, and responsible AI.
Requirements
- Bachelor’s or master’s degree in Computer Science, Data Science, Engineering, or a related technical field; a master’s degree in Data Science is preferred.
- 9–12 years of experience in AI/ML development, advanced analytics, or data-driven software engineering.
- Deep expertise in machine learning algorithms, statistical modeling, neural networks, NLP, or computer vision.
- Strong proficiency in Python and AI/ML libraries including Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, or Keras.
- Hands-on experience designing and deploying ML models into production environments at scale.
- Strong understanding of GenAI techniques, LLMs, embeddings, vector databases, and prompt engineering.
- Proficiency with SQL and large, complex datasets.
- Experience with AWS SageMaker, Azure ML, or Google Vertex AI.
- Familiarity with MLOps tools and practices, including model registries, feature stores, and monitoring frameworks.
- Understanding of distributed computing, microservices, APIs, data engineering, ML security, governance, and responsible AI.
- Experience mentoring technical teams, managing stakeholders, defining AI roadmaps, and communicating complex concepts to technical and non-technical audiences.
Benefits
- Work onsite Monday through Thursday and choose the work location on Fridays based on work requirements.
- Inclusive Wellbeing Program supporting employees and families across physical, social, emotional, and financial well-being.
- Learning and development programs with higher education and certification reimbursement.
- Employee Resource Groups supporting inclusion, belonging, and community.
- Eight hours of paid time off per calendar year for volunteer work with nonprofit charitable organizations.
- Helping Hands Fund supporting employees facing unforeseen personal financial hardship.
- Comprehensive benefits and programs.
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